不精确概率的独立性概念综述

Inés Couso, S. Moral, P. Walley
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引用次数: 181

摘要

本文的目的是澄清不精确概率的独立性的概念。假设两个边缘实验都由一个不精确的概率模型描述,即由概率分布的凸集或等效模型(如上下概率或预估)描述。在此基础上,提出了确定两个实验的独立性和建立联合实验的不精确概率模型的几种方法。我们调查并比较了独立的六种定义。为了阐明这些定义的含义以及它们之间的关系,我们给出了从瓮中抽出球的简单例子。对于每个独立性的概念,我们给出了一个数学定义,一个直观的或行为的解释,一个假设下的定义是合理的,和一个例子,一个瓮模型的定义是适用的。我们学习的每个独立性概念在某些应用中似乎都是有用的。强独立性和认识独立性的概念似乎是最常适用的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A survey of concepts of independence for imprecise probabilities
Our aim in this paper is to clarify the notion of independence for imprecise probabilities. Suppose that two marginal experiments are each described by an imprecise probability model, i.e., by a convex set of probability distributions or an equivalent model such as upper and lower probabilities or previsions. Then there are several ways to define independence of the two experiments and to construct an imprecise probability model for the joint experiment. We survey and compare six definitions of independence. To clarify the meaning of the definitions and the relationships between them, we give simple examples which involve drawing balls from urns. For each concept of independence, we give a mathematical definition, an intuitive or behavioural interpretation, assumptions under which the definition is justified, and an example of an urn model to which the definition is applicable. Each of the independence concepts we study appears to be useful in some kinds of application. The concepts of strong independence and epistemic independence appear to be the most frequently applicable.
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